SPECK
1.0.1Receptor Abundance Estimation using Reduced Rank Reconstruction and Clustered Thresholding
Overview
Surface Protein abundance Estimation using CKmeans-based clustered thresholding ('SPECK') is an unsupervised learning-based method that performs receptor abundance estimation for single cell RNA-sequencing data based on reduced rank reconstruction (RRR) and a clustered thresholding mechanism. Seurat's normalization method is described in: Hao et al., (2021) doi:10.1016/j.cell.2021.04.048, Stuart et al., (2019) doi:10.1016/j.cell.2019.05.031, Butler et al., (2018) doi:10.1038/nbt.4096 and Satija et al., (2015) doi:10.1038/nbt.3192. Method for the RRR is further detailed in: Erichson et al., (2019) doi:10.18637/jss.v089.i11 and Halko et al., (2009) doi:10.48550/arXiv.0909.4061. Clustering method is outlined in: Song et al., (2020) doi:10.1093/bioinformatics/btaa613 and Wang et al., (2011) doi:10.32614/RJ-2011-015.
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- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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- ERROR2026-03-3011 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
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Documentation
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Package metadata
- First published
- 2022-10-13
- Total releases
- 4 / 4 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 1.9 MB / 1 file
- Download size
- 2.4 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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